Experiments on data fusion using headline information

This poster describes initial work exploring a relatively unexamined area of data fusion: fusing the results of retrieval systems whose collections have no overlap between them. Many of the effective meta-search/data fusion strategies gain much of their success from exploiting document overlap across the source systems being merged. When the intersection of the collections is the empty set, the strategies generally degrade to a simpler form. In order to address such situations, two strategies were examined: re-ranking of merged results using a locally run search on the text fragments returned by the source search engines; and re-ranking based on cross document similarity, again using text fragments presented in the retrieved list. Results, from experiments, which go beyond previous work, indicate that both strategies improve fusion effectiveness.